code: def __setitem__(self, i, elem):
      if torch.is_tensor(i) or isinstance(i, np.ndarray):
          i = i.tolist()
      if isinstance(i, int):
          self.list[i] = elem
      elif isinstance(i, (tuple, list)):
          if len(i) != len(elem):
              raise ValueError()
          if isinstance(elem, ObjectPredictionList):
              for ind, el in enumerate(elem.list):
                  self.list[i[ind]] = el
          else:
              for ind, el in enumerate(elem):
                  self.list[i[ind]] = el
      else:
          raise NotImplementedError(f"{type(i)}")
  
imports: from collections.abc import Sequence
  from typing import List, Union
  import numpy
  import torch
  from sahi.annotation import BoundingBox, Category, Mask
  from sahi.prediction import ObjectPrediction
label_desc: Use image node_id 3 for calling the ObjectPredictionList obj's underlying member method code with example usage: obj.__setitem__(i, elem) without return types